Distributed generation (DG) based on renewable energy resources has shown a significant growth facilitated by policy makers, global concerns about climate change, availability of affordable energy shortage technologies, interest in clean energy production, etc. Energy suppliers using power plants based on fossil fuel (e.g., coal, natural gas, etc.) are also investing in an extension of energy generation portfolio by renewable alternatives such as wind turbines and photovoltaic systems.
However, there can be several requirements to be met before such systems can be connected to the utility grid. These requirements are generally published by standardizing institutions, such as IEC and IEEE, but also by local regulating authorities. One of the requirements, mandatory in many parts of the world, is that distributed generators, especially those connected to low voltage distribution grids, should be able to detect islanding conditions.
Islanding refers to a condition of a distributed generator, where the generator continues powering a part of a distribution network even though power from an electric utility is no longer present. FIGS. 1a and 1b show a difference between a grid-connected mode and an islanding mode.
In FIG. 1a, a switching device 1, for example, a circuit breaker or fuse, is closed, and distributed generators operate in grid-connected mode.
In FIG. 1b, the switching device 1 is opened and the lower part 2 of the network is no longer connected to the main grid. If the power generated by the distributed generators closely matches the power required by the load, the network can continue operation in the islanding mode. If the powers do not match closely, under/over voltage and under/over frequency relays of the distributed generators may stop the power generation. Therefore, the probability of having islanding conditions can be very small.
However, unintentional islanding can be dangerous to utility workers, who cannot realize that the particular part of the network on which they are working is still powered even though there is no power from the main grid. Also, islanding can lead to damages to customer equipment, especially in situations of re-closing into an island. For these reasons, distributed generators should be able to detect islanding and immediately stop power production.
There has been a lot of interest in micro-grids, such as distribution grids that can operate in controllable, intentional islanding conditions, decoupled from the main grid. In such grids, islanding detection can also be an important issue. Detection of islanding conditions can be required in order to switch the control modes of distributed generators from power injection to voltage and frequency control during disconnection and vice versa during reconnection to the main grid.
The need for reliable islanding detection combined with development of distributed power generation industry has led to an intensive research and development of methods for identification of islanding conditions. These methods can be categorized in three main groups: passive, active, and communication-based methods.
Passive methods monitor one or more grid variables and, on the basis of deviation of the variables from allowed thresholds, a decision of disconnecting (detection of islanding) can be made. A passive method can look for an abnormal change in, for instance, frequency, voltage or phase angle but also in some particular harmonics or the total harmonic distortion (THD). If the monitoring algorithm detects large or sudden changes of these variables, the method can determine islanding conditions to be present. The islanding conditions can be determined on the basis of a combination of passive methods and multi-criteria decision making.
Passive methods can, for instance, be implemented by an algorithm within the controller of a distributed generator or in a dedicated external device. Passive methods are easy to implement and are quite effective in majority of situations that can occur in the grid.
However, non-detection zones (NDZ) of the passive methods are quite large. In situations where the power absorbed by the load closely matches the power generated by a distributed generator, the variations in voltage, frequency or phase angle can be lower than those specified in the standard because the network remains balanced even though the connection with the main grid has been lost. In such a case, the distributed generator cannot trip when an island has been formed. Passive methods are generally considered as an insufficient means for anti-islanding protection.
Active methods appeared as result of a need to minimize the non-detection zone of islanding detection methods. Active methods deliberately disturb the grid and, on the basis of the grid response to that disturbance (variation of grid electrical quantities), decide whether or not islanding has occurred.
For instance, disturbances in terms of shifts from normal operating values to grid voltage magnitude, frequency, or phase angle can be added by a distributed generator and, in case of grid connected situation, these disturbances should be corrected by the grid through the voltage and frequency control.
However, if a voltage magnitude, frequency or phase angle follow the shift introduced by the distributed generator, it can be determined that the grid has been disconnected, hence an island has been formed.
An active method can, for instance, be implemented using a positive feedback in a controller of a distributed generator. The controller tries to alter grid variables, such as frequency, phase, or voltage magnitude, in order to obtain, for instance, a frequency jump or phase jump, or a frequency bias. If the grid follows the changes generated by the distributed generator, the grid voltage will exceed imposed operating ranges and result in detection of islanding conditions. For instance, if the grid frequency follows the inverter current, an island has formed and the distributed generator should disconnect. Alternatively, a positive voltage feedback altering voltage magnitude at the point of common coupling can also be formed.
Alternatively, non-characteristic harmonics can be injected by the distributed generator and the grid response can be registered. Injection of non-characteristic inter-harmonic current can be used to derive the grid impedance at that particular frequency.
Impedance detection can be used as another active method approach. This approach is promoted by the requirements in the German standard. A current spike can, for instance, be periodically injected at the point of common coupling by a grid tied power converter. The grid impedance value is determined using Fourier transform, on the basis of the voltage response to this disturbance. A phase angle signal used to generate the reference for current controller can also be slightly altered to be able to estimate the grid impedance on the basis of a grid reaction to the generated current. A high frequency signal can also be injected at a zero crossing in order to determine the value of grid impedance, and active and reactive power oscillations can be used in to identify the value of grid impedance.
Although active methods can result in a more reliable islanding identification, they can also distort the delivered power by detecting the islanding conditions. Power system disturbance can be at an unacceptable level when more than one distributed generators are connected on a same feeder.
Because synchronization in respect to the inter-harmonic injection is possible, each distributed generator can inject a unique inter-harmonic in order to enable connection of more than one similar generation units on the same grid. However, only a finite number of distributed generators can be connected on the same feeder. The number of distributed generators directly depends on the standard demands regarding disconnection time and the number of injections necessary to obtain accurate impedance identification.
Large number of distributed generators using active methods can not only decrease the quality of power in the grid but also increase the non-detection zone of all active methods.
Communication-based methods make use of a communication means (owned, for instance, by a distribution system operator) which signalizes operational states of the switching equipment to the distributed generators.
A power line can be used as a carrier for communication between, for instance, a distributed generator and a utility grid. A continuous signal is transmitted by utility network via the power line. A receiver can be placed inside the distributed generator in order to detect a loss of this signal and, hence, islanding.
When a utility re-closer is equipped with a transmitter which communicates with DG when opens, a signal can, alternatively, be produced on disconnect.
Yet another approach is a SCADA (Supervisory Control And Data Acquisition) based method. For instance, voltage sensors can be placed at the location where a distributed generator is connected and those sensors can be integrated in the SCADA system. The SCADA system can then monitor for islanding conditions and alarm the distributed generators to disconnect in case of islanding.
A disadvantage of the communication based methods is that they typically require involvement from utility providers in implementation of islanding detection schemes, thus, making the methods less favorable for practical implementation. Because implementing communication also adds costs to both the distributed generator and the grid infrastructure, these methods are not commonly used today.
Another disadvantage of a SCADA based approach can be a relatively slow response time. For example, a response time for a SCADA system is around 5 to 10 seconds in an event of islanding conditions. This is far behind the typically requested disconnection time imposed by regulations, for example, 2 seconds.
Known electrical power network systems can have difficulties coping with increasing demand for power and need to reduce carbon dioxide emissions. Therefore, a new form of electrical power network systems that can handle these challenges in a sustainable, reliable and economic way is emerging. These networks can, for instance, utilize the same basic electric infrastructure as today, but will also draw on advanced monitoring, control and communications technology.
The result, for instance, can be a smart grid that is largely automated, applying greater intelligence to operate, monitor and even heal itself. The smart grid can be more flexible, more reliable and better able to serve the needs of a digital economy.
The availability of bidirectional communication in smart grid infrastructures combined with the power quality issues brought by active methods, especially when a large number of distributed generators are installed in the grid, can favor the communication based methods for islanding detection.
On the other hand, implementation of communication based methods can depend on cooperation with utility providers. The utility providers can be unwilling to adopt a centralized protection scheme as it could require significant investments from their part.
Additionally, in a smart grid, power can have more than one path to flow on, and the direction of the power can change. This can have a negative influence on the communication based methods listed above. For instance, if power lines are used as carriers for signals, multiple paths for power can cause signals to interfere and cause nuisance tripping of some of the distributed generators. The signals can be set with different frequencies but it can be necessary to ensure that all of the distributed generators located on the feeder listen to all of the used frequencies.
Multiple paths for power can also have an effect on methods where a signal is produced on disconnect. In a known radial network, once a switching device opens, it can send out a trip signal to all generators in the network. However, when multiple flow paths exist, the islanding conditions can depend on the direction of power in the paths. The switch can have to send out the trip signal in either direction. This can cause undesired disconnection of generators from a properly working part of the network.
FIG. 2 illustrates an example of a situation where a network of power electrical units is supplied by a main grid through two substations 1 and 2. The substations 1 and 2 are interconnected through switches 5 and 6.
If switch 3 of the first substation 1 is open and switch 4 of the second substation 4 is closed, power is supplied to the power electrical units from the second substation 4 and the local generators in the network. When switch 5 opens, it should send a trip signal only to generators located in the direction of first substation 1.
However, if the switch 4 of the first substation 1 and the switch 6 are closed and a switch 4 of the second substation 2 is open, switch 5 should send a trip signal only to generators located in the direction of the second substation 2 at disconnect. Thus, it can be very difficult for switch 5 to decide to which generators to send the trip signal.
In smart grids, a much higher sampling rate can be necessary in order for a SCADA approach to become efficient and compliant with the standards. Large sizes of distribution networks can require more space in the SCADA database and faster data processing. Moreover, due to large number of customers of Distribution System Operators, data sent to SCADA system is generally aggregated at a secondary substation level. Thus, concrete information about a particular customer, for instance, a distributed generator, can be non-existent. The situation can change with the installation of smart meters all over the distribution grid. However, the installation of smart meters can challenge the communication bandwidth and speed and data storage if all data is stored at control centre level.